Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Dec 2, 2024
Date Accepted: Sep 4, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Organizing Telemonitoring: a Dutch Case Study on Decision-Making between Centralized and Distributed Models, Using the NASSS Framework
ABSTRACT
Background:
Telemonitoring can be implemented using either centralized or distributed organizational models. However, few published studies explore which conditions make one model preferable over the other, or how to choose between these two.
Objective:
This study investigated the decision-making factors across several domains (e.g. technological, personal, organizational) when selecting the telemonitoring model.
Methods:
We conducted a multiple case study across four purposively sampled hospitals to gain a range of perspectives on organizational models for telemonitoring. Selection criteria included: 1) type of organizational model, 2) presence or absence of collaborating partners, and 3) task division of activities. Data was collected in a document study, 13 semi-structured interviews, and focus group. The interview topic list was based on the domains of the NASSS (non-adoption, abandonment, scale-up, spread, and sustainability) framework. Interviewees were five project leaders, two tele-nurses, four healthcare professionals, and two clinical informaticians. Iterative data analysis integrated document analysis, interview transcripts, and literature abductively. After completing the initial findings, we conducted a member-checking focus group with the five project leaders.
Results:
Various preferential factors based on the seven domains of the NASSS framework were explored for both centralized and distributed telemonitoring models: 1) Condition: The choice of objective, usually based on organizational strategy, determines whether telemonitoring will be centralized or distributed. 2) Technology:. The preference for a model is determined by the anticipated number of notifications the application generates for a specific patient group. 3) Value Proposition: The perceived cost-effectiveness and overall value to the patient shape the value proposition for each model. 4) Adopters: The new role of tele-nurse emerged in centralized monitoring centers (CMCs), necessitating new competencies, task redistribution, and shifts in responsibility. 5) Organization: CMCs are typically organized regionally, in partnerships or network arrangements, which can be time-consuming yet offer significant potential for impact. 6) Wider System: The existing Dutch reimbursement system does not incentivize CMCs because the payment structure is still based on a per-treatment model. 7) Adaption Over Time: With advancements in technology, including artificial intelligence, organizing telemonitoring through CMCs is likely to gain popularity.
Conclusions:
Our study highlights that when decision-makers are choosing which telemonitoring model—centralized and/or distributed—to implement in their organization, deciding on the suitability of the model depends on multiple contextual factors. Our findings illustrate that decisions made for patient group selection, technology design and value proposition significantly influence each other. It is therefore crucial for decision-makers to understand these interactions and corresponding dynamics to better align their strategies with the operational realities of their organization.
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